Simulating effects of variable nitrogen application rates on corn yields and NO[3]-N losses in subsurface drain water
Dates
Year
2000
Citation
BAKHSH,A., KANWAR, R.S., Jaynes, D. B., Colvin, T.S., and Ahuja, L. R., 2000, Simulating effects of variable nitrogen application rates on corn yields and NO[3]-N losses in subsurface drain water: v. 44, no. 2.
Summary
Using a model as a management tool requires testing of the model against field-measured data prior to its application for solving natural resource problems. This study was conducted to test the Root Zone Water Quality Model (RZWQM98) using four years (1996 to 1999) of field-measured data to simulate the effects of different N-application rates on corn yields and nitrate-nitrogen (NO[3]-N) losses via subsurface drain water. Three N-application rates (low, medium, and high), each replicated three times, were applied to corn in 1996 and 1998 under a randomized complete block design at a tile-drained corn-soybean rotation field near Story City, Iowa. No N-fertilizer was applied to soybean in 1997 and 1999. Model calibration and evaluation [...]
Summary
Using a model as a management tool requires testing of the model against field-measured data prior to its application for solving natural resource problems. This study was conducted to test the Root Zone Water Quality Model (RZWQM98) using four years (1996 to 1999) of field-measured data to simulate the effects of different N-application rates on corn yields and nitrate-nitrogen (NO[3]-N) losses via subsurface drain water. Three N-application rates (low, medium, and high), each replicated three times, were applied to corn in 1996 and 1998 under a randomized complete block design at a tile-drained corn-soybean rotation field near Story City, Iowa. No N-fertilizer was applied to soybean in 1997 and 1999. Model calibration and evaluation were based on field measurements of tile flows, NO[3]-N losses in tile water, and corn-soybean yields. On average, the model simulated tile flow, NO[3]-N losses in tile water, and yields by showing a percent difference of -8%, 15%, and -4%, respectively, between measured and simulated values. The simulated yield response function showed that corn grain yields reached a plateau level when the N-application rate exceeded 200 kg-N/ha in 1996 and 170 kg-N/ha in 1998. These results suggest that RZWQM has the potential to simulate the effects of N-application rates on corn yields and NO[3]-N losses with tile water. However, the model overestimated NO[3]-N losses in subsurface drainage water during the soybean growth period, which may require further refinements in the N-cycling algorithm in relation to N[2]-fixation and N-uptake processes.
